DocumentCode
2510349
Title
On-Line Signature Verification Using 1-D Velocity-Based Directional Analysis
Author
Ibrahim, Muhammad Talal ; Kyan, Matthew ; Khan, M. Aurangzeb ; Guan, Ling
Author_Institution
Ryerson Multimedia Res. Lab., Ryerson Univ., Toronto, ON, Canada
fYear
2010
fDate
23-26 Aug. 2010
Firstpage
3830
Lastpage
3833
Abstract
In this paper, we propose a novel approach for identity verification based on the directional analysis of velocity-based partitions of an on-line signature. First, inter-feature dependencies in a signature are exploited by decomposing the shape (horizontal trajectory, vertical trajectory) into two partitions based on the velocity profile of the base-signature for each signer, which offers the flexibility of analyzing both low and high-curvature portions of the trajectory independently. Further, these velocity-based shape partitions are analyzed directionally on the basis of relative angles. Support Vector Machine (SVM) is then used to find the decision boundary between the genuine and forgery class. Experimental results demonstrate the superiority of our approach in on-line signature verification in comparison with other techniques.
Keywords
digital signatures; handwriting recognition; support vector machines; 1D velocity-based directional analysis; high-curvature portions; identity verification; interfeature dependencies; low curvature portions; online signature verification; support vector machine; velocity-based shape partitions; Artificial neural networks; Databases; Forgery; Shape; Support vector machines; Training; Trajectory; curvature; inter-feature dependencies; on-line signature; support vector machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location
Istanbul
ISSN
1051-4651
Print_ISBN
978-1-4244-7542-1
Type
conf
DOI
10.1109/ICPR.2010.933
Filename
5597554
Link To Document